Abstract: Technologies are provided for automated generation of directed content campaigns. The generated campaign can be optimized for performance. In some embodiments, a group of variations of attributes that define a directed content campaign can be generated and allocated traffic weights for respective impressions of the directed content campaign in a media outlet channel. The traffic weights can then be iteratively updated until a termination criterion is satisfied. At each iteration, the traffic weight can be updated by applying a machine-learning model to current performance metric values of respective impressions corresponding to the traffic weights. After termination of the updates to the traffic weights, a particular set of variations having traffic weights exceeding a threshold can be selected as directed content campaign having satisfactory performance. Those variations can be supplied to a requestor device for subsequent utilization.